Enhancing Cyber Physical Resilience of Smart Grids

Cyber Physical Security Analysis of Digital Substations

Securing the Grid Edge: AI-Driven Cybersecurity for DERMS and Critical Infrastructure

The Future of Technology: Navigating the Next Digital Frontier with AI and Cybersecurity

Verifying the eBPF Verifier in the Linux Kernel

Building Trust in AI Driven Security The Case for Explainable Threat Intelligence.

Securing the Bare Metal Control Flow Attestation and Pitfalls in Microcontroller System Design

Biometric Security in the Age of Generative AI: From Anti Spoofing to Health

Fundamentals of Quantum Technologies for Cybersecurity

AI for Social Good in the Era of Large Language Models

Safeguarding Data Confidentiality: From Deniable Encryption to Secure Deletion.

Generative AI including Large Language Models for Cyber Security

Detection of Anomalous Data and Malicious Sensors in Connected and Autonomous Vehicle Networks

Enabling Data Recovery from Ransomware Attacks in Mobile Devices.

Applied Machine Learning and Nonlinear Methods for Cybersecurity.

Enhancing Cybersecurity with AI: Challenges and Opportunities

Interference and incompleteness: an abstract interpretation perspective.

Beyond Cryptography: Challenges and Solutions for Quantum Resistant Protocols in Constrained Systems

Artificial Intelligence Applications for Microarchitectural Side-Channel Attacks

Traffic Analysis Café: Detection Stepping-Stone Intrusions with DeepCoFFEA and ESPRESSO.

Two Machine Learning Based Frameworks for Enhancing Privacy Protection

Enabling Programmable In-Network Security for an Attack-Resilient Microgrid

Towards Networked Cooperative Autonomy

IEEE 4th Cyber Awareness and Research Symposium 2024 ( CARS'24 ) - Opening Remarks

Attack Trends in Critical Infrastructure and Industrial Control Systems

Cyber Security for Everyone

A Workshop on Cyber Infrastructure for the Smart Electric Grid

Security and Safety of Internet-Connected Cyber-Physical Systems

Security, then, now, and future.

Model-based dynamic state estimation and deep learning on graphs for fault detection in microgrids.